【摘要】 利用震前可具备的光学图像与震后卫星SAR图像的信息融合,可检测与评估震灾区地表面建筑物破坏状态。本文根据震前光学图像的建筑物特征参数,通过SAR成像仿真算法,模拟各建筑物SAR图像,根据震后SAR真实图像与SAR仿真图像互信息量的比较,综合利用归一化互信息量、梯度互信息量、区域互信息量及检测与评估建筑物破坏状态。采用2010年海地地震灾前的IKONOS光学图像、灾后COSMO-SkyMed与RADARSAT-2的星载SAR图像,进行震后建筑物破坏状态检测与评估。其结果与震后GeoEye光学图像进行了验证,证明了本文方法的可行性。更多还原

【Abstract】 Quick and accurate evaluation of the building damages after earthquake in urban area is a critical issue for timely assessing the disaster situation and effectively carrying out rescue mission. Very High Resolution (VHR) optical image is usually a direct way to visually monitor natural disaster occurrence. However, under some serious situations, such as bad weather or difficult geographic conditions, the post-event VHR optical image is not always available over large areas. All day and all weather space-borne Synthetic Aperture Radar (SAR) in operation can provide the reliable and high quality images over a large area. Of course, the relationship between optical image and SAR image is not simply a one-to-one visual correspondence. Microwave scattering and penetration through terrain media, and image speckles of SAR observation with a certain resolution are different from VHR optical imaging. How to make fusion of VHR optical and SAR images under different pre-event and post-event situations can provide a useful and operational approach to make timely and accurate evaluation of earthquake losses.更多还原